MobilisedMaps

Inspiration

Durham is a city that is not the most friendly for those with reduced mobility, and the most optimal route provided by Google Maps is not often the one that is viable for most people with disabilities or those with reduced mobility. We wanted to find a way to help pick routes that enables people to enjoy Durham without having to be concerned about whether or not they will actually be able to do so.

What it does

Pulling route data from Google Maps API, we run various statistical models and analysis on a number of routes in output what we feel is a reflective ranking of the route in terms of its ease of use and friendliness.

How we built it

We built it using Python and Google Maps API.

Challenges we ran into

We lost our two front end developers about 4 hours in who were actually able to work with the interface and actually turn it into an app or viable website

It also took a long time to try and figure out what is a suitable basis for creating these rankings and what actually works in terms of various analysis. We utilised our Physics background and applied theories from there to help evaluate routes.

Accomplishments that we're proud of

With limited experience producing apps designed for the non academic public, we produced a prototype product which is addressing the needs of a targeted demographic.

What we learned

Customer research and the difficulties lying within trying to model issues with routes

What's next for MobilisedMaps

A front end so that users can actually interact with the program.

The ability to geo-tag seating spots and benches, whether routes have narrow staircases, cobbled paths etc. and local amenities that are disabled-friendly and incorporate this into the ranking algorithm to further accurately reflect what is a potential optimal route

Fine tuning of the ranking algorithm via user input so it is weighted depending on what is a priority for themselves